Case Study - Geo-Fence
Location Analytics Used to Improve Customer Experience
A hospitality provider improves customer
experience by using cutting-edge
technology to create a competitive
Challenge:Today's hospitality industry is much more commoditized with booking services at the tip of the customers fingertips through a web browser. One of the top ten hospitality providers worldwide is challenged with providing progressively better experiences to set apart their service from other providers. They were challenged with finding new solutions to reducing the time guests wait for assistance for services, understanding frequency and patterns of repeat guests to Food & Beverage outlets, optimizing the use of staff to better accommodate the desires of their guests and providing personalized promotions to guest that meet their preferences.
Solution:This is a very complex challenge that has many possible solutions. We focused on using technology the hotel already had in place and then augmented it with additional technology to come up with a location analytic solution to provide perishable insights to the hotel that they could act on to improve their guests experience. The hotel already had Aruba access points installed throughout the hotel. We added Aruba Airwave and Aruba ALE to provide location tracking of devices that were wi- fi capable. How this works is we established geo-fences in locations that were of high interest to the hotel, such as front desk, restaurant, bar, valet area, lobby, main pool, and meeting rooms. Then when someone with a cell phone enters the hotel the phone sends a message at a fixed frequency that contains information about the phone to the network and the network sends back a little bit of information about the network so if they decide to connect they are ready to do so. The ALE is able to triangulate the signal between access points, which would establish the physical position of the phone within the network. The Aruba ALE was configured to regularly send a 0MQ message with this data encapsulated over a SSL connection to a cloud server that accepted these messages. The received messages were sent through an adapter that transforms the data into events, which are injected in a complex event processor (CEP). This very powerful CEP is setup to listen for location events and then process them based on user defined rules related to the geo-fences established as well as store the events in an in- memory distributed memory store for future use to create historical analytics. The location data is integrated with customer loyalty database data, external systems, administration configuration and historical data to enrich the quality processing.
Results:A solution with a web front end that provides the hotel with a rich set of real-time and historical data that helps them:
- Monitor dwell time of guests vs. staff (in real time) to adjust staffing by sending alerts directly to staff and management.
- Alert management (in real time) of unattended guest in locations that service is required.
- Provide management with historical analysis of path traffic patterns of guest and employees over a 24 hour period.
- Provide analysis of average dwell times and device count of specific areas of the hotel
- Historical heat maps to show the concentration of devices over a period of time in the network.
- Compare analytics of 1st vs. repeat visitors and understand their traffic patterns.
- Track individual events in the meeting rooms and provide analytical data about the dwell time and device count during the event.